IRONICALLY one of the most exciting things to hear at an agricultural technology event was researchers focused on not reinventing the wheel.

While numerous technology start-ups spoke of concepts, accelerators and prototypes at the GFIA In Focus Australia technology event, held in Brisbane, the CSIRO and University of Sydney researchers also focused on leveraging existing technologies.

CSIRO, Data 61 agtech cluster leader for robotics and autonomous systems, Dr Peyman Moghadam said when he began in the agtech space one of the things he noticed was the overwhelming number of drones, robots and new technologies being pitched at farmers without any practical plans for servicing and maintenance.

“We took a different view of the whole technology, could we come up with a way to take existing equipment, existing assets, that had already been on the farm for many years, and make them smarter?” he said.

Dr Moghadam said his group then developed intelligent technologies to adapt a side by side vehicle (SSV), specifically a John Deere Gator, to make it fully autonomous for operations in heavily canopied orchards where existing auto steering technologies often fail due to the lack of reliable GPS signal.

“The first fully autonomous gator has been showcased in the past couple of months in vineyards, macadamia farms and other orchards,” he said.

Dr Moghadam said it was important to leverage off existing sensor technologies from around the globe and from different industries to keep the cost of integration down.

“Australia is the perfect landing pad for start-ups. We get unique opportunities, we are off-season from the rest of the world, if someone is building technology from Europe or the US they come to Australia to test in the off-season.”

Also speaking on the panel, University of Sydney, Australian Centre for Field Robotics, lead systems engineer, Matt Truman said he also believed Australian researchers leveraged overseas technologies well.

“As robotics engineers, we can think of ourselves as systems integrators,” he said.

“We are not designing and building, for example, new sensors, we take the best technology from other industries and integrate it with our robotic platforms.

“Some of the other technologies we use to underpin our research are machine learning, particularly deep learning, which is like a superpower for our computer vision researchers. “It enables things like precision weeding, you can go out in the field and do real-time weed detection, there are open source frameworks and code we can leverage there.”